Business Studies

The reply must summarize the student’s findings and indicate areas of agreement, disagreement, and improvement. It must be supported with scholarly citations in the latest APA format and corresponding list of references. The minimum word count for discussion reply is 275 words.

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Discussion: Variables, Research Questions and Data Coding

D1.1. Compare the terms active independent variables and attribute independent variable.

What are the similarities and differences?

According to Morgan et al. (2020), variables are characteristics of an individual or circumstances that can be studied and measured. Often, they take on different values. Examples of variables include examining an individual’s height, weight, age, or gender. According to the textbook (Morgan et al., 2020), variables must vary or have different components or values within the research study. Variables are measured and can assume values at different levels.

Within the context of a definition, it can be referred to as an unknown quantity in an expression or equation. As Morgan et al. (2020) stated, when variables are considered within quantitative research, they are operationally and often divided into independent, dependent, and extraneous variables.

Active independent variables can be manipulated by the researcher or investigator of the study. The participant may feel as if the investigator manipulates them. According to Morgan et al. (2020), active variables can also be referred to as experimental variables. When an independent variable is considered an active one, the research investigator can manipulate the values and how they affect other variables within the study.

An attribute variable is not altered during the research process. For example, if one was studying the effects of age and exercise routines, one can study the age and the amount of time spent on exercise but not be able to change the participant’s age.

D1.2. What kind of independent variable (active or attribute) is necessary to infer cause? Can one always infer cause from this type of independent variable? If so, why? If not, when can one infer cause and when might casual inferences be more questionable?

The independent variable that is necessary to infer cause is one that is active, according to Morgan et al. (2020). Just because it is active, it does not mean that it can contribute to the cause in all cases. The information within the textbook stated that the only approaches that have active independent variables, which are randomized experimental or extent, quasi-experimental provide data and that allow it to be inferred so that the independent variable causes the change or the difference within the dependent variable (Morgan et al., 2020)

However, when examining the differences between participants with different values of independent attribute variables, one should not conclude that the variables that are attributed independent caused the dependent variable to change (Morgan et al., 2020)

D1.3. What is the difference between the independent variable and the dependent variable?

Morgan et al. (2020) stated that two different types of independent variables exist. They can be active and attribute, and it is critical to one’s research to distinguish between them. An attribute independent variable is one which cannot be manipulated but is still a focus of the research. The definition used by the authors (Morgan et al., 2020) states that independent variables include any predictors and antecedents and can be presumed causes or influences within one’s research. While others refer to independent variables as factors or grouping variables, independent variables are often labeled using the word “variable,” as is the case for dependent variables by some scholars or researchers.

When discussing the types of independent variables and the inferences concerning cause and effect, Morgan et al. (2020) explained that statistical analysis will not differentiate whether the independent variable is an attribute or an active independent variable.

Stating that dependent variables measure or assess the effect of the independent variable, Morgan et al. (2020) explained that it is a thought of a presumed outcome or criterion. When one sees test scores, ratings, measurements, or ratings from questionnaires, these are examples of information gathered and fall under the terms of dependent variables. Unlike independent variables, dependent variables must have at least two values (Morgan et al., 2020).

D1.4 Compare and contract associational, difference, and descriptive types of research questions.

Morgan et al. (2022) stated that when one drafts a difference question it compares two or more different groups. One group consists of individuals holding one of the values or levels of the independent variable. Questions that are different are usually used with comparative designs and can be conducted with randomized experimental designs. This group comparison question is used for randomized experimental, quasi-experimental, and comparative approaches (Morgan et al., 2020). Regarding associational questions, the independent variable is usually continuous or has numerous ordered levels.

According to Morgan et al. (2020), the scores on the independent variable align with the associated dependent variable scores. A description question is one that is associated with a descriptive approach. Scores are associated with their central tendency, variability, or percentages within each level or category and are single variables. When the descriptive question is used within the research data findings, it describes the data and can be used within any research format (Morgan et al., 2020).

Within the information regarding the three types of variables, Morgan et al. (2020) stated that the general purpose of exploring the relationship between variables is used with the difference and associational approaches. In contrast, the description is only used within a descriptive question format. The specific purpose of the difference methodology is to compare groups, where the associational questions find the strength of associations and related variables. Summarizing data is the specific purpose of a description question. The general type of statistic found within the difference format is inferential statistics such as tests and ANOVA. Correlation and regression are examples of Associational Inferential statistics and within descriptive statistic is the mean, percentage, and range (Morgan et al., 2020).

D1.5. Write a research question and a corresponding hypothesis regarding variables of interest to you but not in the HSB dataset. Is it an associational, difference, or descriptive question?

D1.5a. An example of an associational question would be: Is there an association between hair color and winners of the Miss America Scholarship Pageant?

D1.5b. Are there different pageant systems in regard to age of participant?

D1.5c. What is the average age and hair color of pageant winners?

D1.6. Using one or more of the following HSB variables, religion, mosaic pattern test, and visualization score

Write an associational question.
What is the association between religion and the mosaic pattern test?

Write a difference question.
Are there any differences between the mosaic pattern test scores from various religions?

Write a descriptive question.
Which religion score higher on the mosaic pattern test? Which one score the lowest?

References
Morgan, G. A., Barrett, K. C., Leech, N. L., & Gloeckner, G. W. (2020). IBM SPSS for introductory statistics: Use and interpretation, sixth edition (6th ed.). Routledge.

ANSWER

Variables, Research Questions, and Data Coding

I believe that you made an excellent point regarding the differences between active independent and attribute variables. The manipulation aspect is one of the essential elements that highlights the status of a variable. During the research process, the investigator can alter the variable depending on the circumstances or experience a situation where the variable cannot be manipulated. I also agree that the independent active variable is one that is likely to infer cause since it exists within the active status (Morgan et al., 2020). This means that the variable is exposed to alterations likely to generate a distinct outcome. The major difference between dependent and independent variable is that the dependent is the cause while the latter is the study aspect. As Andrade (2021) states, the dependent variable is influenced in value by other variables while the independent one influences the value of others. Researchers must always ensure that they highlight the relationship between the dependent and the independent variable.

The analysis of the major similarities and differences of the questions allows the audience to verse themselves with the insights surrounding these vital question frameworks. One of the aspects that I admire about descriptive questions is their ability to portray an in-depth analysis of the issue or event at hand. These questions encompass definitional information which offer the audience with a better understanding of the issue under study. The key foundation behind effective outcomes lies with quality questions (Agee, 2009). I also believe that the formulated questions align with the established frameworks. For instance, the association type question shows the link between hair color and Miss American Scholarship Pageant. If the people who win the award have a specific type of hair, this means that the award is likely to be won by this segment.

References

Agee, J. (2009). Developing qualitative research questions: A reflective process. International journal of qualitative studies in education, 22(4), 431-447. https://doi.org/10.1080/09518390902736512

Andrade, C. (2021). A student’s guide to the classification and operationalization of variables in the conceptualization and design of a clinical study: Part 1. Indian Journal of Psychological Medicine, 43(2), 177-179. https://doi.org/10.1177/0253717621994334

Morgan, G. A., Barrett, K. C., Leech, N. L., & Gloeckner, G. W. (2020). IBM SPSS for introductory statistics: Use and interpretation, sixth edition (6th ed.). Routledge.